Singing in the Shower Playlists:
| Playlist Name | ID | Songs |
|---|---|---|
| Songs to Sing in the Shower | 37i9dQZF1DWSqmBTGDYngZ | 70 |
| Shower / sing-a-long | 1rmsEzwr6ZmRNzCUph24vZ | 81 |
| Shower | 1dTgSkYRwILdvmckibB9AP | 440 |
Pop Playlists:
| Playlist Name | ID | Songs |
|---|---|---|
| Pop Hits 2000-2018 | 6mtYuOxzl58vSGnEDtZ9uB | 293 |
| Pop Hits Rewind | 0RPcfl1sCsJ03B0bztuKAn | 70 |
| Guilty Pleasures | 37i9dQZF1DX4pUKG1kS0Ac | 151 |
| Mega Hit Mix | 37i9dQZF1DXbYM3nMM0oPk | 75 |
This corpus will represent playlists with generally similar songs, but that are or are not classified as ‘singing in the shower’ playlists. By comparing these groups, I will try to see if there is a measurable difference in certain attributes measured by Spotify, to define what it means to be a ‘singing in the shower’ playlist. I chose the most-followed ‘singing in the shower’ playlists on Spotify, so I believe it should be a good representation of music that people do enjoy while showering.
Looking at this first scatterplot, we see the greatest concentration of music, for both playlists, in the quadrant with high energy and high valence. This seems valid, given both playlists seem to have a large mix of fast-paced, loud, and cheerful music. As such, we can see our first real similarity in both playlists.
More interestingly, we see that the ‘singing in the shower’ playlists have a wider array of music. Particularly, it seems to have a decent proportion of songs with 0-0.5 valence, as compared to the ‘pop’ playlist. One theory for this is that top charts ‘pop’ music is generally “catchy” because it has a positive and fast beat, but songs that people generally like to sing along to can be happy or more angry, that usually have fast and loud beats. Neither, however, seem to have much music with low energy and low valence, but music in that category tends to be perceived as sadder, which makes it less likely to be considered a ‘pop’ song, and also most likely makes it not as fun to sing in the shower (though this is mere speculation on my behalf).
Both playlists have some notable differences in peak energy and acousticness densities. However, the tempo and loudness density distributions are almost identical!
Looking at the most popular song from each set of playlists:
In a preliminary analysis of the plots, we can see that ‘Perfect’ has more dense chroma features. It also has noticeable use of pitch classes Bb, F, and Eb, unlike ‘7 rings’. On the other hand, ‘7 rings’ uses pitch classes A and F#, unlike ‘Perfect’. It’s interesting to see how different the most popular song from each playlist is just based on chroma values.
The differences noted in the previous storyboard between the top song from each playlist are even more noticeable when comparing the chroma and timbre self-similarities matrices of both songs. The most noticeable difference is that ‘Perfect’ has more points of novelty / changes throughout the song, whereas ‘7 rings’ has few unexpected parts of the song (where the biggest change is at the start of the song). Rather, ‘7 rings’ is far more homogenous. That said, both songs have few texture changes, and have mostly consistent song structures, if you exclude the beginning of both songs.